Perencanaan pembelajaran skills lab di STIKES PKU Muhammadiyah Surakarta
Bibliographic record
Abstract
Pembelajaran skill lab sangat dibutuhkan untuk meningkatkan kemampuan dan kompetensi keperawatan. Penelitian ini bertujuan menggambarkan bagaimana perencanaa, pembelajaran skills lab di di STIKES PKU Muhammadiyah Surakarta. Penelitian ini merupakan penelitian kualititaf dengan menggunakan pendekatan deskriptif. Pengambilan data dilaksanakan dengan beberapa cara yaitu: Focus group discussion melibatkan 12 mahasiswa keperawatan semester 2; wawancara dengan 7 informan; Observasi pembelajaran skill lab dan studi dokumentasi. Selanjutnya data dianalisis dengan metode analisis kualitatif. Hasil penelitian menunjukkan bahwa perencanaan skill lab keperawatan meliputi sumber daya manusia, kurikulum, fasilitas, mahasiswa dan sosialisasi. Kesimpulan penelitian bahwa perencanaan pembelajaran skills lab telah dilakukan dengan sistematis. Perencanaan pembelajaran skills lab harus selalu dilakukan untuk meningkatkan kualitas pembelajaran dan keterampilan mahasiswa keperawatan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".